Interaction Mechanism Research Articles

MicroRNAs regulate the vicious cycle of vascular calcification-osteoporosis in postmenopausal women.

Menopause is a normal physiological process accompanied by changes in various physiological states. The incidence of vascular calcification (VC) increases each year after menopause and is closely related to osteoporosis (OP). Although many studies have investigated the links between VC and OP, the interaction mechanism of the two under conditions of estrogen loss remains unclear. MicroRNAs (miRNAs), which are involved in epigenetic modification, play a critical role in estrogen-mediated mineralization. In the past several decades, miRNAs have been identified as biomarkers or therapeutic targets in diseases. Thus, we hypothesize that these small molecules can provide new diagnostic and therapeutic approaches. In this review, we summarize the close interactions between VC and OP and the role of miRNAs in their interplay.

From data to discovery: AI-guided analysis of disease-relevant molecules in spinal muscular atrophy (SMA).

Spinal Muscular Atrophy is caused by partial loss of survival of motoneuron (SMN) protein expression. The numerous interaction partners and mechanisms influenced by SMN loss result in a complex disease. Current treatments restore SMN protein levels to a certain extent, but do not cure all symptoms. The prolonged survival of patients creates an increasing need for a better understanding of SMA. Although many SMN-protein interactions, dysregulated pathways, and organ phenotypes are known, the connections among them remain largely unexplored. Monogenic diseases are ideal examples for the exploration of cause-and-effect relationships to create a network describing the disease-context. Machine learning tools can utilize such knowledge to analyze similarities between disease-relevant molecules and molecules not described in the disease so far. We used an artificial intelligence-based algorithm to predict new genes of interest. The transcriptional regulation of 8 out of 13 molecules selected from the predicted set were successfully validated in an SMA mouse model. This bioinformatic approach, using the given experimental knowledge for relevance predictions, enhances efficient targeted research in SMA and potentially in other disease settings.

Identification of Microorganism in Infected Wounds by Positively Charged Selective Sensor Array and Deep Learning Algorithm.

Microorganism are ubiquitous and intimately connected with human health and disease management. The accurate and fast identification of pathogenic microorganisms is especially important for diagnosing infections. Herein, three tetraphenylethylene derivatives (S-TDs: TBN, TPN, and TPI) featuring different cationic groups, charge numbers, emission wavelengths, and hydrophobicities were successfully synthesized. Benefiting from distinct cell wall binding properties, S-TDs were collectively utilized to create a sensor array capable of imaging various microorganisms through their characteristic fluorescent signatures. Furthermore, the interaction mechanism between S-TDs and different microorganisms was explored by calculating the binding energy between S-TDs and cell membrane/wall constituents, including phospholipid bilayer and peptidoglycan. Using a combination of the fluorescence sensor array and a deep learning model of residual network (ResNet), readily differentiation of Gram-negative bacteria (G-), Gram-positive bacteria (G+), fungi, and their mixtures was achieved. Specifically, by extensive training of two ResNet models with large quantities of images data from 14 kinds of microorganism stained with S-TDs, identification of microorganism was achieved at high-level accuracy: over 92.8% for both Gram species and antibiotic-resistant species, with 90.35% accuracy for the detection of mixed microorganism in infected wound. This novel method provides a rapid and accurate method for microbial classification, potentially aiding in the diagnosis and treatment of infectious diseases.

Atomistic simulations of the interaction of edge dislocations with β-Nb precipitates in Zr-Nb alloys

Experiments have shown that precipitation can affect the mechanical properties of zirconium alloy, but the interaction mechanism between dislocations and Nb precipitates in zirconium alloys is still unclear. Thus, a systematic molecular dynamics study was performed to investigate the interaction between edge dislocations and Nb precipitates. It was found that the dislocation passed through Nb precipitate by shear mechanism or bypass mechanism of forming jogs, and the critical resolved shear stress increased with the diameter of the precipitate. After completion of the interaction, dislocations formed jogs due to climb when the precipitates were larger than 2 or 3 nm. Some atoms in the precipitate were more disordered after dislocation shearing, and dislocation fragments were generated around the precipitate, both of which lead to the precipitate hardening. The calculation of obstacle strength further confirmed that unsheared Nb precipitates until hundreds of nanometers were the weak obstacle for dislocations.

Cooperative Vehicle Infrastructure System or Autonomous Driving System? From the Perspective of Evolutionary Game Theory

In this paper, we explore the trade-offs between public and private investment in autonomous driving technologies. Utilizing an evolutionary game model, we delve into the complex interaction mechanisms between governments and auto manufacturers, focusing on how strategic decisions impact overall outcomes. Specifically, we predict that governments may opt for strategies such as constructing and maintaining infrastructure for Roadside Infrastructure-based Vehicles (RIVs) or subsidizing high-level Autonomous Driving Vehicles (ADVs) without additional road infrastructure. Manufacturers’ choices involve deciding whether to invest in RIVs or ADVs, depending on governmental policies and market conditions. Our simulation results, based on scenarios derived from existing economic data and forecasts on technology development costs, suggest that government subsidy policies need to dynamically adjust in response to manufacturers’ shifting strategies and market behavior. This dynamic adjustment is crucial as it addresses the evolving economic environment and technological advancements, ensuring that subsidies effectively incentivize the desired outcomes in autonomous vehicle development. The findings of this paper could serve as valuable decision-making tools for governments and auto manufacturers, guiding investment strategies that align with the dynamic landscape of autonomous driving technology.

Simultaneous Nitrogen Removal and Phosphorus Recovery by Anammox-Induced Magnesium Phosphate Mineralization: Interaction Mechanism between Microorganisms and Mineral Formation

Simultaneous Nitrogen Removal and Phosphorus Recovery by Anammox-Induced Magnesium Phosphate Mineralization: Interaction Mechanism between Microorganisms and Mineral Formation

Dynamic responses of reinforced concrete silo considering pile–soil‐structure–granular solid interaction

SummaryThe columned‐supported reinforced concrete silo models with different filling conditions considering soil‐structure dynamic interaction (SSI) are established based on the finite element program ANSYS to thoroughly investigate the complex interaction mechanism of the soil–pile–silo structure with granular solid. The dynamic characteristics and seismic responses of the SSI system and fixed‐base condition are analyzed and compared when the filling conditions are empty‐filled state, half‐filled state and full‐filled state. The numerical results reveal that the SSI effect reduces the seismic acceleration response of columned‐supported silos effectively. However, in terms of displacement, the SSI effect often amplifies the relative deformation of the supporting column and the cylindrical silos. Furthermore, the SSI effect often increases the relative dynamic lateral pressure of the storage material in the half‐filled silo condition. In the full‐filled silo condition, the relative dynamic lateral pressure at the top and bottom of the storage material is increased by the SSI effect; while it is decreased in the middle part of the granular solid, demonstrating that the SSI effect could change and increase the seismic responses of the silo structure in certain areas. Therefore, the investigation provides a comprehensive insight into the interaction mechanism of the pile–soil–silo structure with different filling conditions.

Physical Integrated Digital twin-based Interaction Mechanism of Artificial Intelligence Rehabilitation Robots Combining Visual Cognition and Motion Control

Physical Integrated Digital twin-based Interaction Mechanism of Artificial Intelligence Rehabilitation Robots Combining Visual Cognition and Motion Control

Decomposition of complex interactions in graphene oxide-superplasticizer-cement composites and proposed guidelines for sample preparation and assessment

Despite the recognized potential of graphene oxide (GO) in reinforcing and functionalizing cement composites, the commercialization of GO-incorporated cement composites still faces enormous challenges due to the huge variation on reported performance improvement among existing research. This phenomenon is largely attributed to the complex interactions in the GO-superplasticizer-cement system and the absence of standardized guidelines for sample preparation and performance assessment. To address these concerns, this study thoroughly designs a series of cement composites to decompose the ternary interaction with in-depth comparative analyses. Based on the results of workability and compressive strength, an interaction mechanism within the GO-superplasticizer-cement system is proposed and subsequently cross-validated. In addition, reinforcement efficiencies for each scenario are systemically assessed and summarized, effectively covering the majority of cases outlined in the prevailing literature. Accordingly, guidelines for sample preparation and evaluation in research related to GO-incorporated cement composites are developed.

Exploring the mechanism of interaction of glipizide with DNA: Combined in vitro and bioinformatics approach

DNA, vital for biological processes, encodes hereditary data for protein synthesis, shaping cell structure and function. Since revealing its structure, DNA has become a target for various therapeutically vital molecules, spanning antidiabetic to anticancer drugs. These agents engage with DNA-associated proteins, DNA–RNA hybrids, or bind directly to the DNA helix, triggering diverse downstream effects. These interactions disrupt vital enzymes and proteins essential for maintaining cell structure and function. Analysing drug–DNA interactions has significantly advanced our understanding of drug mechanisms. Glipizide, an antidiabetic drug, is known to cause DNA damage in adipocytes. However, its extract mechanism of DNA interaction is unknown. This study delves into the interaction between glipizide and DNA utilizing various biophysical tools and computational technique to gain insights into the interaction mechanism. Analysis of UV–visible and fluorescence data reveals the formation of complex between DNA and glipizide. The binding affinity of glipizide to DNA was of moderate strength. Examination of thermodynamic parameters at different temperatures suggests that the binding was entropically spontaneous and energetically favourable. Various experiments such as thermal melting assays, viscosity measurement, and dye displacement assays confirmed the minor grove nature of binding of glipizide with DNA. Molecular dynamics studies confirmed the glipizide forms stable complex with DNA when simulated by mimicking the physiological conditions. The binding was mainly favoured by hydrogen bonds and glipizide slightly reduced nucleotide fluctuations of DNA. The study deciphers the mechanism of interaction of glipizide with DNA at molecular levels.

Synthesis of Composite Sorbents with Chitosan and Varied Silica Phases for the Adsorption of Anionic Dyes

In this work, various types of silica materials were used for the synthesis of chitosan–silica composites. The composites were obtained using the chitosan (Ch) immobilization process from an aqueous solution on various silica phases, i.e., amorphous diatomite (ChAD), crystalline diatomite (ChCD), mesoporous silica MCM-41 (ChMCM), and mesoporous silica SBA-15 (ChSBA). Textural, structural, morphological, and surface properties of the materials were determined by using various measurement techniques, i.e., low-temperature adsorption/desorption isotherms of nitrogen, X-ray diffraction (XRD), small-angle X-ray scattering (SAXS), potentiometric titration, high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM). The adsorption properties towards various anionic dyes, i.e., acid red 88 (AR88), acid orange 8 (AO8), and orange G (OG), were evaluated based on kinetic and equilibrium measurements. The ChSBA, ChAD, and ChMCM composites were characterized by relatively high adsorption capacities (am) for AR88, with values equal to 0.78, 0.71, and 0.69 mmol/g, respectively. These composites were also distinguished by the rapid AR88 adsorption rate, with the values of half-time parameter t0.5 equal to 0.35, 2.84, and 1.53 min, respectively. The adsorption equilibrium and kinetic data were analyzed by applying the generalized Langmuir isotherm and the multi-exponential equation (m-exp), respectively. An interaction mechanism between the dyes and the obtained materials was proposed.

Retention of ZnO nanoparticles onto polypropylene and polystyrene microplastics: Aging-associated interactions and the role of aqueous chemistry

Microplastics (MPs) are pervasive and undergo environmental aging processes, which alters potential interaction with the co-contaminants. However, to assess their contaminant-carrying capacity, mimicking the weathering characteristics of secondary MPs is crucial. To this end, this study investigated the interaction of Zinc oxide (nZnO) nanoparticles with non-irradiated (NI) and UV-irradiated (UI) forms of the most abundant MPs in aqueous environments such as polypropylene (PP) and polystyrene (PS). SEM images revealed mechanical abrasions on the surfaces of NI-MPs and their subsequent photoaging caused the formation of close-ended and open-ended cracks in UI-PP and UI-PS, respectively. Batch-sorption experiments elucidated nZnO uptake kinetics by on PP and PS MPs, suggesting a sorption-desorption pathway due to weaker and stronger sorption sites until equilibrium was achieved. UI-PP showed higher nZnO (∼3000 mg/kg) uptake compared to NI-PP, while UI-PS showed similar or slightly decreased nZnO (∼2000 mg/Kg) uptake compared to NI-PS. FTIR spectra and zeta potential measurements revealed electrostatic interaction as the dominant interaction mechanism. Higher nZnO uptake by MPs was noted between pH 6.5 and 8.5, whereas it decreased beyond this range. Despite DOM, MPs always retained ∼874 mg/kg nZnO irrespective of MPs type and extent of aging. In the case of humic acids, complex synthetic and natural water matrices, NI-MPs retained higher nZnO than UI-PS, suggesting that photoaged MPs sorb less nZnO under environmental conditions than non-photoaged MPs. These findings enhance our understanding on interaction of MPs with co-contaminants in natural environments.

Study of the dynamic interactions between helix-stiffened cement mixing piles and soft soil under oblique incidence of SV waves in arbitrary space

Helix stiffened cement mixing (HSCM) piles are extensively utilized in soft soil sites due to their excellent seismic and pullout resistance. Initially, the equivalent nodal force formulas for each face under the oblique incidence of SV waves in any spatial direction are derived based on the viscous-spring artificial boundary. The method's applicability in studying pile–soil interactions is verified based on existing pile–soil tests. Subsequently, the HSCM pile–soil model is constructed using finite element software through a Python program. Various analyses of accelerations, relative displacements, soil reactions, and pile–soil dynamic p-y curves are conducted using two different directions of incidence angles (horizontal and vertical) and various types of seismic waves. Subsequently, the backbone line of the dynamic p-y curve is plotted, revealing the pile–soil interaction mechanism under spatial oblique incidence. Finally, Matlock's formula is modified to ensure its applicability to pile–soil interactions under spatially oblique incidence. The results demonstrate that loading the Kobe wave causes the peak acceleration in the x direction, the peak pile–soil relative displacement, and the peak pile-side soil reaction force to increase by 22.64 %, −18.90 % and 18.42 %, respectively, compared to those of the El Centro wave.

Quantitative Assessment, Molecular Docking and Novel Metabolic Pathways Reveal the Interaction Mechanisms between Norfloxacin biodegradation and Environmental Implications

Quantitative Assessment, Molecular Docking and Novel Metabolic Pathways Reveal the Interaction Mechanisms between Norfloxacin biodegradation and Environmental Implications

Advanced Ru/Ti4O7 catalyst for Tolerating CO and H2S poisoning to hydrogen oxidation reaction

CO and H2S poisoning of Pt-based catalysts for hydrogen oxidation reaction (HOR) stands as one of the long-standing hindrances to the widespread commercialization of proton exchange membrane fuel cells. In this paper, a Ru/Ti4O7 catalyst is successfully synthesized by the microwave-thermal method. This Ru/Ti4O7 catalyst shows a much higher noble metal mass activity than those of commercial PtRu/C and conventional Ru/C catalysts. The performance of the Ru/Ti4O7 catalyst under the exist of CO or H2S shows insignificant current decay, which is far superior to commercial PtRu/C and Pt/C catalysts. In this Ru/Ti4O7 catalyst, the electron transfer between Ru and Ti to form d-p orbital hybridization is considered to be responsible for the favorable catalytic HOR performance and the corresponding CO and H2S tolerance. The interaction mechanism formed by electron transfer may open a promising way for the subsequent development of anti-poisoning catalysts for PEM fuel cell hydrogen oxidation reaction.

Sulfite Ion and Gold (111) Surface Interaction Mechanism

Sulfite Ion and Gold (111) Surface Interaction Mechanism

Efficient and sensitive determination of storage time-temperature marker 5-hydroxy methyl furfural in bee honey based on Fluorescence quenching of human serum albumin

5-hydroxymethyl furfural (HMF) exhibits mutagenic and DNA strand-breaking activity. It is a useful tool to evaluate the effect of heat and time on foodstuffs processing. The fluorescence interaction of HMF with HSA has not been explored to date. Therefore, this work reports the interaction mechanism of HMF with HSA via fluorescence spectroscopy analysis in a simulated physiological environment. The experimental tries showed that HMF intensely quenched the native fluorescence of HSA via the dynamic quenching. According to fluorescence quenching calculations, the binding constants Kb are 1.26x10-4, 2.71x10-4 and 3.19x10-4 M-1 at 298, 303 and 308 K respectively, and the number of binding sites n is almost 1. Thermodynamic parameters values expose that both electrostatic and hydrophobic interactions are accountable for the interaction of HSA and HMF. The presented quenching method for the assay of HMF exhibited a good linearity in the range of 0.1 to 6.66 µg/mL with a detecting limit of 0.0184 µg/mL. These values made the developed method appropriate to be used in the estimation of HMF in samples of bee honey after its extraction using SupelcleanTM ENVI™ -18 SPE Tube. Five bee honey samples show a positive response of HMF after exposing these samples for inappropriate storage or extreme heating.

Entangling imidazolium-based ionic liquids and melanins: A crossover study on chemical vs electronic properties and carrier transport mechanisms

Melanins (mel) are a class of pigments that are nearly ubiquitous and among the oldest compounds found in nature. However, their practical application has been limited due to their low solubility in water and in most organic solvents. Recent research on polydopamine has revealed that ionic liquids (ILs) not only enhance melanin’s dissolution but also fine-tune its redox properties through specific dipolar interactions. In this study, we expand upon previous investigations by customizing new suspensions on a broader range of melanins. Concerning ILs, we focus on imidazolium based ILs, tailoring their chemical properties (pKa) and structural characteristics (cation radius, anion radius).The melanins under consideration include synthetic polymers derived from the oxidative polymerization of 5,6-dihydroxyindole (DHI) and its 2-carboxylic acid counterpart (DHICA), as well as the natural pigment Sepiomelanin (Sepiomel), which is isolated from the ink sack of cuttlefish. Our comparative analysis between neat ILs and ILs-mel responses reveals several key findings: the increase in solubility, the tuning of the redox ability, the decrease of the ionic charge resistance (from MΩ τo kΩ); the partial removal of the electrical polarization effects and the delocalized ionic charge hopping mechanisms in conductivity; the increase of the free ionic diffusion mobility and Debye lengths. Notably, electrical transport is influenced by both the chemical features and the steric hindrance in the ILs as well as the specific type of melanin employed. These factors contribute to the high order correlation between free ionic charge densities and their corresponding Debye lengths. Consequently, our findings suggest that for these complex systems, an improved model extending beyond a simplified electrostatic interaction mechanism is required.

Analysis on the mechanics and deformation of side pile structure in metro station with the PBA method

There are few researches on the interaction mechanism between the buckling load of the side pile top and the soil pressure behind pile (SPP) and the side pile structure. While the side pile structure is the key component of the lining structure of the metro with pile-beam-arch (PBA) method, which plays a very important role in the mechanical stability and deformation control of the lining system of station. Therefore, relying on the metro project about Guangzhou Metro Line 11, this paper investigates the influence law of mechanical characteristics and deformation of the side pile structure of the station with PBA method, taking into account the factors such as different buckling loads (including horizontal load of arch (HLA) and vertical load of arch (VLA)) and SPP, and puts forward corresponding construction suggestions. It is found that the lateral displacement and deformation of side pile structure are controlled by the HLA, and the optimal HLA is 1200kN. The influence of HLA on the bending moments about side pile are greater than that of the axial force. The VLA has more significant effect on vertical settlement of side pile, but little effect on lateral deformation about pile body. The SPP has significant impact on the stability of side pile structure, so it is recommended to take appropriate lining measures to ensure the stability of side pile structure when the SPP is too large.

An Empirical Study on Downstream Dependency Package Groups in Software Packaging Ecosystems

The role of focal packages in packaging ecosystems is crucial for the development of the entire ecosystem, as they are the packages on which other packages depend. However, the evolution of dependency groups in packaging ecosystems has not been systematically investigated. In this study, we examine the downstream dependency package groups (DDGs) in three typical packaging ecosystems—Cargo for Rust, Comprehensive Perl Archive Network for Perl, and RubyGems for Ruby—to identify their features and evolution. We also identify and analyze a special type of DDG, the collaborative downstream dependency package group (CDDG), which requires shared contributors. Our findings show that the overall development of DDGs, particularly CDDGs, is consistent with the status of the whole ecosystem, and the size of DDGs and CDDGs follows a power law distribution. Furthermore, the interaction mechanisms between focal packages and downstream packages differ between ecosystems, but focal packages always play a leading role in the development of DDGs and CDDGs. Finally, we investigate predictive models for the development of CDDGs in the next stage based on their features, and our results show that random forest and Gradient Boosting Regression Tree achieve acceptable prediction accuracy. We provide the raw data and scripts used for our analysis at https://github.com/onion616/DDG.